Measurement of Protein Synthesis Rate in Rat by [11C]Leucine PET Imaging: Application to the TgF344-AD Model of Alzheimer's Disease.

Long-term memory requires stable protein synthesis and is altered in Alzheimer's disease (AD). This study aimed to implement a method to measure the cerebral protein synthesis rate (PSR) with [11C]leucine PET in vivo in rats and evaluate potential PSR alterations longitudinally (6, 12 and 18 months old) in the TgF344-AD rat model of AD. Wistar, wild-type (WT) and TgF344-AD rats (TG) were scanned for 60 min with [11C]leucine. Arterial blood activity was monitored online and with discrete whole blood and plasma samples by γ-counting in Wistar rats, WT (n = 4) and TG (n = 5). Unlabelled amino acids were measured in plasma. The sensitivity of [11C]leucine PET to measure alterations in PSR was assessed in Wistar rats by injection of PSR inhibitor anisomycin before PET acquisition. Anisomycin administration significantly reduced the net uptake rate constant (Kcplx) of [11C]leucine and PSR, proving the suitability of the method. For the longitudinal study, averaged population-based input functions were used to calculate PSR. We found a significant genotype effect on PSR (decrease in TG vs WT) only in the globus pallidus. This study suggests that [11C]leucine PET is sensitive enough to measure brain PSR in rat but that cross-sectional design with individual input function should be preferred.

Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software.

PURPOSE: A novel phantom-imaging platform, a set of software tools, for automated and high-precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed. METHODS: The key feature of this platform is the vector graphics design that facilitates the automated measurement of the knife-edge response function and hence image resolution, using composite volume of interest templates in a 0.5 mm resolution grid applied to all inserts of the phantom. Furthermore, the proposed platform enables the generation of an accurate µ $\mu$ -map for PET/MR systems with a robust alignment based on two-stage image registration using specifically designed PET templates. The proposed platform is based on the open-source NiftyPET software package used to generate multiple list-mode data bootstrap realizations and image reconstructions to determine the precision of the two-stage registration and any image-derived statistics. For all the analyses, iterative image reconstruction was employed with and without modeled shift-invariant point spread function and with varying iterations of the ordered subsets expectation maximization (OSEM) algorithm. The impact of the activity outside the field of view (FOV) was assessed using two acquisitions of 30 min each, with and without the activity outside the FOV. RESULTS: The utility of the platform has been demonstrated by providing a standard and an advanced phantom analysis including the estimation of spatial resolution using all cylindrical inserts. In the imaging planes close to the edge of the axial FOV, we observed deterioration in the quantitative accuracy, reduced resolution (FWHM increased by 1-2 mm), reduced contrast, and background uniformity due to the activity outside the FOV. Although it slows convergence, the PSF reconstruction had a positive impact on resolution and contrast recovery, but the degree of improvement depended on the regions. The uncertainty analysis based on bootstrap resampling of raw PET data indicated high precision of the two-stage registration. CONCLUSIONS: We demonstrated that phantom imaging using the proposed methodology with the metric of spatial resolution and multiple bootstrap realizations may be helpful in more accurate evaluation of PET systems as well as in facilitating fine tuning for optimal imaging parameters in PET/MR and PET/CT clinical research studies.

Guidance for reading FDG PET scans in dementia patients.

18F-2-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) is a powerful method for detection of disease-related impairment of cerebral glucose metabolism in neurodegenerative diseases. It is of particular interest for early and differential diagnosis of dementia. Reading FDG PET scans requires training to recognise deviations from normal functional brain anatomy and its variations. This paper provides guidance for displaying FDG PET brain scans in a reproducible manner that allows reliable recognition of characteristic disease-related metabolic changes. It also describes typical findings in Alzheimer's disease, Frontotemporal Dementia and Dementia with Lewy Bodies and possible confounding factors, such as vascular changes and brain atrophy. It provides a brief overview on findings in other neurodegenerative diseases and addresses the potential and limitations of software packages for comparison of individual scans with reference data.

The effect of 18F-florbetapir dose reduction on region-based classification of cortical amyloid deposition.

UNLABELLED: There are specific dose recommendations for diagnostic amyloid PET imaging with 18F-florbetapir, but they may not apply to research studies using regional quantitative analysis. We, therefore, studied the effect of tracer dose reduction on the discriminative power of regional analysis. METHODS: Using bootstrap resampling of list-mode data from 18F-florbetapir scans, a total of 800 images were reconstructed for four different dosage levels: 100, 50, 20, and 10%. The effect of the injected dose on the variation of measured radiotracer uptake was determined in large cortical regions defined on co-registered and segmented magnetic resonance images. The impact of the observed variation on the discrimination between normal controls and patients with AD was then assessed using data in a cohort study described by Fleisher et al. (Arch Neurol 68(11):1404-1411, 2011). RESULTS: The coefficient of variance for the cortex to cerebellum uptake ratio increased from 0.9% at full dose of 300 MBq to 2.5% at 10% of this dose, but was still small compared to biological variation. It, therefore, had very little impact on discrimination between AD and elderly controls. The original area under the ROC curve was 0.881, decreasing to 0.878 at 10% of full dose. Original sensitivity for discrimination between AD and controls was 82.0%, while specificity was 77.3%; these decreased to 81.8 and 77.1%, respectively, at the reduced dose. However, the number of subjects within the classification border zone between proven amyloid pathology and young healthy controls increased substantially by 7 to 14%. CONCLUSION: A substantial reduction of tracer dose increases uncertainty at the classification border zone while still providing good discrimination between AD patients and controls when using activity data from cortical regions defined on co-registered and segmented MR scans.

The added value of 18-fluorodeoxyglucose-positron emission tomography in the diagnosis of the behavioral variant of frontotemporal dementia.

UNLABELLED: Characteristic frontotemporal abnormalities on structural or functional neuroimaging are mandatory for a diagnosis of probable behavioral variant of frontotemporal dementia (bvFTD) according to the new criteria. 18-Fluorodeoxyglucose-positron emission tomography (18F-FDG-PET) imaging is commonly reserved for patients with suspected bvFTD without characteristic structural neuroimaging results. We studied the diagnostic value of 18F-FDG-PET in these patients. METHODS: The 18F-FDG-PET was performed in 52 patients with suspected bvFTD but lacking characteristic structural neuroimaging results. The clinical diagnosis of bvFTD in the presence of functional decline (bvFTD/fd+) after a follow-up period of 2 years was used as a golden standard. RESULTS: The sensitivity of 18F-FDG-PET for bvFTD/fd+ was 47% at a specificity of 92%. The differential diagnosis comprised alternative neurodegenerative and psychiatric disorders and a benign phenocopy of bvFTD. CONCLUSIONS: The 18F-FDG-PET is able to identify nearly half of the patients with bvFTD who remain undetected by magnetic resonance imaging. In our selected group, high specificity enables exclusion of psychiatric and other neurodegenerative disorders.

Regional neuronal network failure and cognition in late-onset sporadic Alzheimer disease.

BACKGROUND AND PURPOSE: The severe cognitive deficits in Alzheimer disease are associated with structural lesions in gray and white matter in addition to changes in synaptic function. The current investigation studied the breakdown of the structure and function in regional networks involving the Papez circuit and extended neocortical association areas. MATERIALS AND METHODS: Cortical volumetric and diffusion tensor imaging (3T MR imaging), positron-emission tomography with (18)F fluorodeoxyglucose on a high-resolution research tomograph, and comprehensive neuropsychological assessments were performed in patients with late-onset sporadic Alzheimer disease, those with mild cognitive impairment, and elderly healthy controls. RESULTS: Atrophy of the medial temporal lobes was the strongest and most consistent abnormality in patients with mild cognitive impairment and Alzheimer disease. Atrophy in the temporal, frontal, and parietal regions was most strongly related to episodic memory deficits, while deficits in semantic cognition were also strongly related to reductions of glucose metabolism in the posterior cingulate cortex and temporoparietal regions. Changes in fractional anisotropy within white matter tracts, particularly in the left cingulum bundle, uncinate fasciculus, superior longitudinal fasciculus, and inferior fronto-occipital fasciculus, were significantly associated with the cognitive deficits in multiple regression analyses. Posterior cingulate and orbitofrontal metabolic deficits appeared to be related to microstructural changes in projecting white matter tracts. CONCLUSIONS: Many lesioned network components within the Papez circuit and extended neocortical association areas were significantly associated with cognitive dysfunction in both mild cognitive impairment and late-onset sporadic Alzheimer disease. Hippocampal atrophy was the most prominent lesion, with associated impairment of the uncinate and cingulum white matter microstructures and hippocampal and posterior cingulate metabolic impairment.

The Road Ahead to Cure Alzheimer's Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations.

Alzheimer's disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group's revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aß) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard ("core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aß1-42 (Aß1-42), also expressed as Aß1-42 : Aß1-40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for "prodromal AD" and "mild cognitive impairment due to AD" include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in regions of interest, such as the hippocampus and in an exploratory fashion, observer and hypothesis-indedendent, throughout the entire brain. Evolving modalities such as diffusion-tensor imaging (DTI) and advanced tractography as well as resting-state functional MRI provide useful additionally useful measures indicating the degree of fiber tract and neural network disintegration (structural, effective and functional connectivity) that may substantially contribute to early detection and the mapping of progression. These modalities require further standardization and validation. The use of molecular in vivo amyloid imaging agents (the fifth validated biomarker), such as the Pittsburgh Compound-B and markers of neurodegeneration, such as fluoro-2-deoxy-D-glucose (FDG) (as the sixth validated biomarker) support the detection of early AD pathological processes and associated neurodegeneration. How to use, interpret, and disclose biomarker results drives the need for optimized standardization. Multimodal AD biomarkers do not evolve in an identical manner but rather in a sequential but temporally overlapping fashion. Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker severity (degree of abnormality) versus time. AD biomarkers can be combined to increase accuracy or risk. A list of genetic risk factors is increasingly included in secondary prevention trials to stratify and select individuals at genetic risk of AD. Although most of these biomarker candidates are not yet qualified and approved by regulatory authorities for their intended use in drug trials, they are nonetheless applied in ongoing clinical studies for the following functions: (i) inclusion/exclusion criteria, (ii) patient stratification, (iii) evaluation of treatment effect, (iv) drug target engagement, and (v) safety. Moreover, novel promising hypothesis-driven, as well as exploratory biochemical, genetic, electrophysiological, and neuroimaging markers for use in clinical trials are being developed. The current state-of-the-art and future perspectives on both biological and neuroimaging derived biomarker discovery and development as well as the intended application in prevention trials is outlined in the present publication.

Comparison of MRI based and PET template based approaches in the quantitative analysis of amyloid imaging with PIB-PET.

RATIONALE: [(11)C]Pittsburgh compound-B (PIB) has been the most widely used positron emission tomography (PET) imaging agent for brain amyloid. Several longitudinal studies evaluating the progression of Alzheimer's disease (AD), and numerous therapeutic intervention studies are underway using [(11)C]PIB PET as an AD biomarker. Quantitative analysis of [(11)C]PIB data requires the definition of regional volumes of interest. This investigation systematically compared two data analysis routes both using a probabilistic brain atlas with 11 bilateral regions. Route 1 used individually segmented structural magnetic resonance images (MRI) for each subject while Route 2 used a standardised [(11)C]PIB PET template. METHODS: A total of 54 subjects, 20 with probable Alzheimer's disease (AD), 14 with amnestic Mild Cognitive Impairment (MCI) and 20 age-matched healthy controls, were scanned at two imaging centres either in London (UK) or in Turku (Finland). For all subjects structural volumetric MRI and [(11)C]PIB PET scans were acquired. Target-to-cerebellum ratios 40 min to 60 min post injection were used as outcome measures. Regional read outs for grey matter target regions were generated for both routes. Based on a composite neocortical, frontal, posterior cingulate, combined posterior cingulate and frontal cortical regions, scans were categorised into either 'PIB negative' (PIB-) or 'PIB positive' (PIB+) using previously reported cut-off target-to-cerebellar ratios of 1.41, 1.5 and 1.6, respectively. RESULTS: Target-to-cerebellum ratios were greater when defined with a [(11)C]PIB PET template than with individual MRIs for all cortical regions regardless of diagnosis. This difference was highly significant for controls (p<0.001, paired samples t-test), less significant for MCIs and borderline for ADs. Assignment of subjects to raised or normal categories was the same with both routes with a 1.6 cut-off while with lower cut off using frontal cortex, and combined frontal cortex and posterior cingulate demonstrated similar results, while posterior cingulate alone demonstrated significantly higher proportion of controls as amyloid positive by Route 2. CONCLUSIONS: Definition of cortical grey matter regions is more accurate when individually segmented MRIs (Route 1) were used rather than a population-based PET template (Route 2). The impact of this difference depends on the grey-to-white matter contrast in the PET images; specifically seen in healthy controls with high white matter and low grey matter uptake. When classifying AD, MCI and control subjects as normal or abnormal using large cortical regions; discordance was found between the MRI and template approach for those few subjects who presented with cortex-to-cerebellum ratios very close to the pre-assigned cut-off. However, posterior cingulate alone demonstrated significant discordance in healthy controls using template based approach. This study, therefore, demonstrates that the use of a [(11)C]PIB PET template (Route 2) is adequate for clinical diagnostic purposes, while MRI based analysis (Route 1) remains more appropriate for clinical research.

Quantitative evaluation of white matter tract DTI parameter changes in gliomas using nonlinear registration.

Diffusion tensor imaging (DTI) has been used extensively to investigate white matter architecture in the brain. In the context of neurological disease, quantification of DTI data sets enables objective characterisation of the associated pathological changes. The aim of this study is to propose a method of evaluating DTI parameter changes in gliomas in the internal capsule using nonlinear registration to delineate the white matter and enable quantitative assessment of DTI derived parameters. 20 patients selected pre-operatively with probable grade 2 or grade 3 glioma on structural MRI along with ten normal volunteers were included in this study. DTI fractional anisotropy (FA) maps were used to define a common segmented FA skeleton that was projected back onto the original individual FA maps. Objective segment classification as normal or abnormal was achieved by comparison to prediction intervals of FA and mean diffusivity (MD) defined in normal subjects. The internal capsules of each patient were segmented into 10 regions of interest (ROI) with 20 and 16 segments across the group having significantly increased or decreased FA and MD values respectively. Seven glioma patients had abnormal DTI parameters in the internal capsule. We show that the classification of tract segments was consistent with disruption, oedema or compression. The results suggest that this method could be used to detect changes in eloquent white matter tracts in individual patients.

Verification of predicted robustness and accuracy of multivariate analysis.

The assessment of accuracy and robustness of multivariate analysis of FDG-PET brain images as presented in [Markiewicz, P.J., Matthews, J.C., Declerck, J., Herholz, K., 2009. Robustness of multivariate image analysis assessed by resampling techniques and applied to FDG-PET scans of patients with Alzheimer's disease. Neuroimage 46, 472-485.] using a homogeneous sample (from one centre) of small size is here verified using a heterogeneous sample (from multiple centres) of much larger size. Originally the analysis, which included principal component analysis (PCA) and Fisher discriminant analysis (FDA), was established using a sample of 42 subjects (19 Normal Controls (NCs) and 23 Alzheimer's disease (AD) patients) and here the analysis is verified using an independent sample of 166 subjects (86 NCs and 80 ADs) obtained from the ADNI database. It is shown that bootstrap resampling combined with the metric of the largest principal angle between PCA subspaces as well as the deliberate clinical misdiagnosis simulation can predict robustness of the multivariate analysis when used with new datasets. Cross-validation (CV) and the .632 bootstrap overestimated the predictive accuracy encouraging less robust solutions. Also, it is shown that the type of PET scanner and image reconstruction method has an impact on such analysis and affects the accuracy of the verification sample.

Biodistribution, pharmacokinetics and metabolism of interleukin-1 receptor antagonist (IL-1RA) using [¹8F]-IL1RA and PET imaging in rats.

BACKGROUND AND PURPOSE: Positron emission tomography (PET) has the potential to improve our understanding of the preclinical pharmacokinetics and metabolism of therapeutic agents, and is easily translated to clinical studies in humans. However, studies involving proteins radiolabelled with clinically relevant PET isotopes are currently limited. Here we illustrate the potential of PET imaging in a preclinical study of the biodistribution and metabolism of ¹8F-labelled IL-1 receptor antagonist ([¹8F]IL-1RA) using a novel [¹8F]-radiolabelling technique. EXPERIMENTAL APPROACH: IL-1RA was radiolabelled by reductive amination on lysine moieties with [¹8F]fluoroacetaldehyde. Sprague-Dawley rats were injected intravenously with [¹8F]IL-1RA and imaged with a PET camera for 2 h. For the study of IL-1RA metabolites by ex vivoγ-counting of samples, rats were killed 20 min, 1 h or 2 h after injection of [¹8F]IL-1RA. KEY RESULTS: [¹8F]IL-1RA distribution into the major organs of interest was as follows: kidneys >> liver > lungs >> brain. In lungs and liver, [¹8F]IL-1RA uptake peaked within 1 min post-injection then decreased rapidly to reach a plateau from 10 min post-injection. In the brain, the uptake exhibited slower pharmacokinetics with a smaller post-injection peak and a plateau from 6 min onward. IL-1RA was rapidly metabolized and these metabolites represented ∼40% of total activity in plasma and ∼80% in urine, 20 min after injection. CONCLUSIONS AND IMPLICATIONS Preclinical PET imaging is a feasible method of assessing the biodistribution of new biological compounds of therapeutic interest rapidly. The biodistribution of [¹8F]IL-1RA reported here is in agreement with an earlier study suggesting low uptake in the normal brain, with rapid metabolism and excretion via the kidneys.

Robustness of correlations between PCA of FDG-PET scans and biological variables in healthy and demented subjects.

In neuroimaging it is helpful and useful to obtain robust and accurate estimates of relationships between the image derived data and separately derived covariates such as clinical and demographic measures. Due to the high dimensionality of brain images, complex image analysis is typically used to extract certain image features, which may or may not relate to the covariates. These correlations which explain variance within the image data are frequently of interest. Principal component analysis (PCA) is used to extract image features from a sample of 42 FDG PET brain images (19 normal controls (NCs), 23 Alzheimer's disease (AD) patients). For the first three most robust PCs, the correlation of the PC scores with: i) the Mini Mental Status Exam (MMSE) score and ii) age is examined. The key aspects of this work is the assessment of: i) the robustness and significance of the correlations using bootstrap resampling; ii) the influence of the PCA on the robustness of the correlations; iii) the impact of two intensity normalization methods (global and cerebellum). Results show that: i) Pearson's statistics can lead to overoptimistic results. ii) The robustness of the correlations deteriorate with the number of PCs. iii) The correlations are hugely influenced by the method of intensity normalization: the correlation of cognitive impairment with PC1 are stronger and more significant for global normalization; whereas the correlations with age were strongest and more robust with PC2 and cerebellar normalization.

Performance of FDG PET for detection of Alzheimer's disease in two independent multicentre samples (NEST-DD and ADNI).

AIM: We investigated the performance of FDG PET using an automated procedure for discrimination between Alzheimer's disease (AD) and controls, and studied the influence of demographic and technical factors. METHODS: FDG PET data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) [102 controls (76.0 +/- 4.9 years) and 89 AD patients (75.7 +/- 7.6 years, MMSE 23.5 +/- 2.1) and the Network for Standardisation of Dementia Diagnosis (NEST-DD) [36 controls (62.2 +/- 5.0 years) and 237 AD patients (70.8 +/- 8.3 years, MMSE 20.9 +/- 4.4). The procedure created t-maps of abnormal voxels. The sum of t-values in predefined areas that are typically affected by AD (AD t-sum) provided a measure of scan abnormality associated with a preset threshold for discrimination between patients and controls. RESULTS: AD patients had much higher AD t-sum scores compared to controls (p < 0.01), which were significantly related to dementia severity (ADNI: r = -0.62, p < 0.01; NEST-DD: r = -0.59, p < 0.01). Early-onset AD patients had significantly higher AD t-sum scores than late-onset AD patients (p < 0.01). Differences between databases were mainly due to different age distributions. The predefined AD t-sum threshold yielded a sensitivity and specificity of 83 and 78% in ADNI and 78 and 94% in NEST-DD, respectively. CONCLUSION: The automated FDG PET analysis procedure provided good discrimination power, and was most accurate for early-onset AD.

Robustness of multivariate image analysis assessed by resampling techniques and applied to FDG-PET scans of patients with Alzheimer's disease.

For finite and noisy samples extraction of robust features or patterns which are representative of the population is a formidable task in which over-interpretation is not uncommon. In this work, resampling techniques have been applied to a sample of 42 FDG PET brain images of 19 healthy volunteers (HVs) and 23 Alzheimer's disease (AD) patients to assess the robustness of image features extracted through principal component analysis (PCA) and Fisher discriminant analysis (FDA). The objective of this work is to: 1) determine the relative variance described by the PCA to the population variance; 2) assess the robustness of the PCA to the population sample using the largest principal angle between PCA subspaces; 3) assess the robustness and accuracy of the FDA. Since the sample does not have histopathological data the impact of possible clinical misdiagnosis on the discrimination analysis is investigated. The PCA can describe up to 40% of the total population variability. Not more than the first three or four PCs can be regarded as robust on which a robust FDA can be build. Standard error images showed that regions close to the falx and around ventricles are less stable. Using the first three PCs, sensitivity and specificity were 90.5% and 96.9% respectively. The use of resampling techniques in the evaluation of the robustness of many multivariate image analysis methods enables researchers to avoid over-analysis when using these methods applied to many different neuroimaging studies often with small sample sizes.

Education and occupation as proxies for reserve in aMCI converters and AD: FDG-PET evidence.

BACKGROUND: Previous reports have shown that higher education is associated with more severe brain pathology in patients with Alzheimer disease (AD), suggesting that these individuals have a functional reserve provided by education, which masks the clinical expression of a higher degree of neurodegeneration. It is unknown if a similar reserve mechanism exists in patients with amnestic mild cognitive impairment (aMCI). The aim of this study was to assess the impact of education and occupation on brain glucose metabolism (rCMRglc) measured with FDG-PET in aMCI and in a very large sample of subjects with probable AD (pAD). METHODS: A total of 242 patients with pAD, 72 with aMCI, and 144 healthy controls participated in the study. At follow-up, 21 subjects with aMCI progressed to AD. A regression analysis was conducted (SPM2), with education and occupation as independent variables, and rCMRglc as dependent variable, adjusting for demographic data, global cognitive status, and neuropsychological scores. RESULTS: The analysis showed a significant association between higher education/occupation and lower rCMRglc in posterior temporoparietal cortex and precuneus in pAD and aMCI converters, and no correlation in aMCI nonconverters and healthy controls. This means that, when submitted to FDG-PET for diagnostic evaluation, pAD and aMCI converters with higher education/occupation had, for comparable cognitive impairment, a more severe rCMRglc reduction than the ones with lower education/occupation. CONCLUSIONS: This study suggests that education and occupation may be proxies for brain functional reserve, reducing the severity and delaying the clinical expression of Alzheimer disease (AD) pathology. The results in aMCI converters suggest that functional reserve is already at play in the predementia phase of AD.

CSF total and phosphorylated tau protein, regional glucose metabolism and dementia severity in Alzheimer's disease.

BACKGROUND AND PURPOSE: We investigated associations between severity of cognitive impairment, cerebrospinal fluid (CSF) concentrations of total-tau (t-tau) protein and tau phosphorylated at threonin 181 (p-tau(181)) and regional glucose metabolism measured with 18F-fluorodeoxyglucose-positron emission tomography (18F-FDG-PET) in patients with probable Alzheimer's disease (AD). METHODS: In 38 patients (mean age 66.5 +/- 8.0 years) with AD, Mini-Mental State Examination (MMSE) scores were evaluated and CSF levels of t-tau and p-tau(181) measured. All patients underwent an 18F-FDG-PET scan. Image analysis including correlation analysis and principal component analysis (PCA) were performed using SPM5 and VINCI. RESULTS: Dementia severity (MMSE 21.2 +/- 4.9) correlated well with metabolic impairment especially in left hemisphere association areas that are typically affected in patients with AD (e.g. inferior parietal lobule, r = 0.512; medial temporal gyrus, r = 0.478; inferior temporal gyrus, r = 0.488; precuneus, r = 0.468; PCA: r = 0.639, F = 7.751; all P < 0.001). There were no associations between t-tau and p-tau(181) with dementia severity and only weak correlations between t-tau and cerebral glucose metabolism (superior parietal gyrus, r = -0.325, P < 0.05; precentral gyrus r = -0.418, P < 0.01; amygdala r = -0.362, P < 0.05). No correlations were found between p-tau(181) and regional hypometabolism in FDG-PET. CONCLUSION: MMSE and CSF t-tau represent different aspects of disease severity. Whilst MMSE is closely related to impaired cerebral glucose metabolism, CSF t-tau is less closely related and appears to be less well suited for assessment of disease progression.

A comparison of unawareness in frontotemporal dementia and Alzheimer's disease.

BACKGROUND: Loss of insight is a core diagnostic feature of frontotemporal dementia (FTD) and anosognosia is frequently reported in Alzheimer's disease (AD). AIM: To compare unawareness (anosognosia) for different symptoms, measured with a discrepancy score between patient's and caregiver's assessment, in AD and FTD. METHOD: In a prospective, multi-centre study, 123 patients with probable AD, selected according to the NINCDS-ADRDA procedure, were matched for age, sex, education, disease duration and dementia severity to patients with FTD (n = 41), selected according to international consensus criteria. A research complaint questionnaire was used to obtained patient's and caregiver's assessment concerning neuropsychological and behavioural symptoms. Data were compared in each group and between groups. Unawareness (measured by discrepancy scores) was compared between patients with AD and FTD. RESULTS: The caregivers generally assessed symptoms more severely than did patients, but both patient groups reported changes in affect (depressive mood or irritability) as their caregivers did. Unawareness was greater in patients with FTD than in patients with AD for language and executive difficulties, and for changes in behaviour and daily activities. CONCLUSION: The main finding is that unawareness was observed in both patients with FTD and patients with AD for most clinical domains. However, qualitative and quantitative differences showed that lack of awareness was greater in patients with FTD.

Imaging of acetylcholine esterase activity in brainstem nuclei involved in regulation of sleep and wakefulness.

Positron emission tomography with 11C-N-methyl-4-piperidyl-acetate (MP4A) was applied in eight healthy volunteers and two patients with mild Alzheimer's disease (AD) to assess acetylcholine esterase (AChE) activity in magnetic resonance imaging-identified brainstem nuclei. Uptake ratios in lateral dorsal tegmental and pedunculopontine nuclei relative to cerebellum yielded reproducible values for the AChE activity in controls and reduced values in AD, more marked in a patient with complaints of disturbed sleep. Cortical AChE activity was related to the extent of cognitive impairment which was more severe in the AD patient without sleep disturbance. This preliminary observational study demonstrates the feasibility to image and assess AChE activity in small nuclei of the brain stem. This approach may be helpful to investigate the interaction of various nuclei in the complex network regulating sleep and wakefulness in representative patient groups with documented sleep disturbance.

Role of in vivo imaging of the central nervous system for developing novel drugs.

Over the past decade imaging technologies employed in clinical neurosciences have significantly advanced. Imaging is not only used for the diagnostic work-up of neurological disorders but also crucial to follow up on therapeutic efforts. Using disease-specific imaging parameters, as read-outs for the efficiency of individual therapies, has facilitated the development of various novel treatments for neurological disease. Here, we review various imaging technologies, such as cranial computed tomography (CT), magnetic resonance imaging (MRI) and spectroscopy (MRS), positron emission tomography (PET) and single-photon emission computed tomography (SPECT), with respect to their current applications in non-invasive disease phenotyping and the measurement of therapeutic outcomes in neurology. In particular, applications in neuro-oncology, Parkinson's disease, Alzheimer's disease, and cerebral ischemia are discussed. Non-invasive imaging provides further insights into the molecular pathophysiology of human diseases and facilitates the design and implementation of improved therapies.